Description: Performs the arc cosine operation on each element of the input matrix and outputs the result.
Formula:
[object Object]and[object Object]implement the same function in different ways. Select a proper operator based on your requirements.[object Object]: An output tensor object needs to be created to store the computation result.[object Object]: No output tensor object needs to be created, and the computation result is written in place to the input tensor's memory.
Each operator has calls. First,
[object Object]or[object Object]is called to obtain the workspace size required for computation and the executor covering the operator computation process. Then,[object Object]or[object Object]is called to perform computation.[object Object][object Object][object Object][object Object]
Parameters:
[object Object](aclTensor*, computation input): aclTensor on the device. When its data type is INT8, INT16, INT32, INT64, UINT8, or BOOL, the data type is cast to FLOAT32 for computation, and the output is of the FLOAT32 type. It supports . Its can be ND. For a non-contiguous tensor, its dimensions cannot exceed 8, and its shape must be the same as that of[object Object].- [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be INT8, INT16, INT32, INT64, UINT8, BOOL, FLOAT, BFLOAT16, FLOAT16, or DOUBLE.
- [object Object]Atlas training products[object Object] and [object Object]Atlas inference products[object Object]: The data type can be INT8, INT16, INT32, INT64, UINT8, BOOL, FLOAT, FLOAT16, or DOUBLE.
[object Object](aclTensor*, computation output): aclTensor on the device. It supports . Its can be ND. For a non-contiguous tensor, its dimensions cannot exceed 8, and its shape must be the same as that the input tensor.- [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be FLOAT, BFLOAT16, FLOAT16, or DOUBLE.
[object Object]Atlas training products[object Object] and [object Object]Atlas inference products[object Object]: The data type can be FLOAT, FLOAT16, or DOUBLE.
[object Object](uint64_t*, output): size of the workspace to be allocated on the device.[object Object](aclOpExecutor**, output): operator executor, covering the operator computation process.
Returns:
Parameters:
[object Object](void*, input): address of the workspace to be allocated on the device.[object Object](uint64_t, input): size of the workspace to be allocated on the device, which is obtained by calling[object Object].[object Object](aclOpExecutor*, input): operator executor, covering the operator computation process.[object Object](aclrtStream, input): stream for executing the task.
Returns:
Parameters:
[object Object](aclTensor*, computation input/output): input/output tensor, that is,[object Object]and[object Object]in the formula. It is the aclTensor on the device. It supports . Its can be ND. For a non-contiguous tensor, its dimensions cannot exceed 8.- [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be FLOAT, BFLOAT16, FLOAT16, or DOUBLE.
[object Object]Atlas training products[object Object] and [object Object]Atlas inference products[object Object]: The data type can be FLOAT, FLOAT16, or DOUBLE.
[object Object](uint64_t*, input): size of the workspace to be allocated on the device.[object Object](aclOpExecutor**, input): operator executor, covering the operator computation process.
Returns:
Parameters:
[object Object](void*, input): address of the workspace to be allocated on the device.[object Object](uint64_t, input): size of the workspace to be allocated on the device, which is obtained by calling[object Object].[object Object](aclOpExecutor*, input): operator executor, covering the operator computation process.[object Object](aclrtStream, input): stream for executing the task.
Returns:
- Deterministic computation:
[object Object]and[object Object]each default to a deterministic implementation.
The following example is for reference only. For details, see .